BUG: Addition operation between NaN and list returns NaN
- [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.

---
```python
>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame({'c1':[[1,2,3]], 'c2':[np.nan]})
>>> df
          c1  c2
0  [1, 2, 3] NaN
>>> df.c1 + df.c2
0    NaN
dtype: object
>>> [1, 2, 3] + np.nan
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: can only concatenate list (not "float") to list
```

#### Problem description

In Pandas when using the "+" operator on a Series entry containing a list and a Series entry containing a NaN value, a NaN value is returned. This is inconsistent with standard Python where attempting to concatenate a list and a NaN raises a TypeError. In general, list concatenation between a NaN and a list is an ambiguous operation and therefore should raise an error.

#### Expected Output

A TypeError should be raised.

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

<details>

INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
python           : 3.7.4.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.18362
machine          : AMD64
processor        : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.2.4
numpy            : 1.19.5
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.1.1
setuptools       : 52.0.0.post20210125
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : 4.0.1
blosc            : None
feather          : None
xlsxwriter       : 1.2.8
lxml.etree       : 4.5.0
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 3.0.0
IPython          : 7.16.1
pandas_datareader: None
bs4              : 4.8.0
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.4
numexpr          : None
odfpy            : None
openpyxl         : 3.0.1
pandas_gbq       : None
pyarrow          : 0.17.1
pyxlsb           : None
s3fs             : None
scipy            : 1.6.2
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
numba            : None

</details>
