BUG: iloc.__setitem__ with a numpy array throws a TypeError expecting 1-D list
- [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.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

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

```python
# Your code here
import numpy as np
import pandas as pd

dfx = pd.DataFrame({'a': np.ones(10)}) 
dfx.iloc[np.array([0]), np.array([0])] = np.array([[2]]) # works
dfx['a_I'] = dfx['a'].astype('Int64') 
dfx = dfx[["a_I"]] 
dfx.iloc[np.array([0]), np.array([0])] = np.array([[2]]) # doesn't work
```

#### Problem description

The second case should set the value to 2.

#### Expected Output

I have narrowed the problem down to here: 

https://github.com/pandas-dev/pandas/blob/dec736f3fcc3337bea0ee180ee28f73e5bf54939/pandas/core/indexing.py#L1768

The dimension of the `indexer` is being increased in that call.

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.8.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.3.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.18.1
pytz             : 2018.5
dateutil         : 2.7.3
pip              : 19.2.3
setuptools       : 42.0.2
Cython           : 0.29.10
pytest           : 5.4.1
hypothesis       : None
sphinx           : 2.4.4
blosc            : None
feather          : 0.4.0
xlsxwriter       : None
lxml.etree       : 4.5.0
html5lib         : None
pymysql          : None
psycopg2         : 2.8.3 (dt dec pq3 ext lo64)
jinja2           : 2.11.1
IPython          : 7.0.1
pandas_datareader: None
bs4              : 4.8.2
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.0
matplotlib       : 3.2.0
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : 0.13.1
pyarrow          : 0.16.0
pytables         : None
pytest           : 5.4.1
pyxlsb           : None
s3fs             : 0.4.0
scipy            : 1.4.1
sqlalchemy       : 1.3.15
tables           : 3.6.1
tabulate         : None
xarray           : 0.15.0
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : None
numba            : 0.48.0

</details>
