BUG: "None" not recognized with vectorized equality
- [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
>>> import pandas as pd
>>> df = pd.DataFrame( { 'foo':['a','b','c'], 'bar':[1,3,2] } )
>>> df.iloc[1,0] = None
>>> df
    foo  bar
0     a    1
1  None    3
2     c    2
>>> df['foo'] == None
0    False
1    False
2    False
Name: foo, dtype: bool
>>> df['foo'].apply( lambda x: x == None )
0    False
1     True
2    False
Name: foo, dtype: bool
>>>
```

#### Problem description

One expects the `==` operator to distribute/vectorize over pandas columns.  In this case, it appears to do so, returning a bool for each value in the column, but those results are not what one would expect.  Indeed, one can use an apply (as shown above) to verify that the answer from the vectorized version is not correct.

#### Expected Output

That `df['foo'] == None` should match `df['foo'].apply( lambda x: x == None )`.

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

<details>

INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
python           : 3.7.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
Version          : Darwin Kernel Version 18.7.0: Mon May  3 20:41:19 PDT 2021; root:xnu-4903.278.68~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.4
numpy            : 1.19.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.2
setuptools       : 49.6.0.post20200814
Cython           : 0.29.17
pytest           : 6.0.1
hypothesis       : 5.24.0
sphinx           : 2.4.0
blosc            : None
feather          : None
xlsxwriter       : 1.2.9
lxml.etree       : 4.5.2
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : 1.3.2
fsspec           : 0.7.4
fastparquet      : None
gcsfs            : None
matplotlib       : 3.1.3
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.4
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.0
sqlalchemy       : 1.3.18
tables           : 3.6.1
tabulate         : 0.8.3
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.50.1

</details>
