BUG: ValueError is mistakenly raised if a numpy array is assigned to a pd.Series of dtype=object and both have the same length
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
import pandas as pd
import numpy as np

pd.__version__ #  '1.1.3'
pdseries = pd.Series(index=[1,2,3,4], dtype=object)
pdseries.loc[1] = np.zeros(100)  # this works fine
pdseries.loc[3] = np.zeros(4)     # this raises a value error because len(pdseries)==len(np.zeros(4))
```

TypeError: only size-1 arrays can be converted to Python scalars
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
  File "/Users/daniel/.conda/envs/production_system/lib/python3.7/site-packages/IPython/core/interactiveshell.py", line 2878, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-40-460230264bf1>", line 1, in <module>
    pdseries.loc[3] = np.zeros(4)
  File "/Users/daniel/.conda/envs/production_system/lib/python3.7/site-packages/pandas/core/indexing.py", line 670, in __setitem__
    iloc._setitem_with_indexer(indexer, value)
  File "/Users/daniel/.conda/envs/production_system/lib/python3.7/site-packages/pandas/core/indexing.py", line 1802, in _setitem_with_indexer
    self.obj._mgr = self.obj._mgr.setitem(indexer=indexer, value=value)
  File "/Users/daniel/.conda/envs/production_system/lib/python3.7/site-packages/pandas/core/internals/managers.py", line 534, in setitem
    return self.apply("setitem", indexer=indexer, value=value)
  File "/Users/daniel/.conda/envs/production_system/lib/python3.7/site-packages/pandas/core/internals/managers.py", line 406, in apply
    applied = getattr(b, f)(**kwargs)
  File "/Users/daniel/.conda/envs/production_system/lib/python3.7/site-packages/pandas/core/internals/blocks.py", line 887, in setitem
    values = values.astype(arr_value.dtype, copy=False)
ValueError: setting an array element with a sequence.

#### Problem description

It is possible to assign (numpy) arrays to elements of pandas.Series ofd type=object. Unfortunately, in case the array is of the same size as the Series a ValueError is raised.

How can one avoid this error?

#### Expected Output

The interesting thing is that the assignment takes place as expected:
In[42]: pdseries
Out[42]: 
1    [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...
2                                                  NaN
3                                 [0.0, 0.0, 0.0, 0.0]
4                                                  NaN

One might argue that a warning could be useful but an error is misleading and tricky to debug.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : db08276bc116c438d3fdee492026f8223584c477
python           : 3.7.8.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Mon Aug 31 22:12:52 PDT 2020; root:xnu-6153.141.2~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.UTF-8
pandas           : 1.1.3
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.4
setuptools       : 49.6.0.post20201009
Cython           : 0.29.21
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : 2.8.6 (dt dec pq3 ext lo64)
jinja2           : 2.11.2
IPython          : 5.8.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.2.1
sqlalchemy       : 1.3.20
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
