BUG: value_counts and nunique behave differently for NaN and None with dropna=False
- [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

```python
s = pd.Series([None, np.nan, 'Y'])
s.nunique(dropna=False)
s.value_counts(dropna=False)
```

#### Problem description

nunique returns 3, but value_counts only has 2 rows. This may be related to Issue https://github.com/pandas-dev/pandas/issues/37566

#### Expected Output

I would expect these to be consistent.

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

<details>

pandas           : 1.3.0
numpy            : 1.19.5
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 21.1.2
setuptools       : 56.0.0
Cython           : 0.29.23
pytest           : 6.2.3
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.3
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.24.1
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 0.8.5
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.1
numexpr          : 2.7.3
odfpy            : None
openpyxl         : 3.0.6
pandas_gbq       : None
pyarrow          : 3.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.6.2
sqlalchemy       : 1.3.23
tables           : None
tabulate         : None
xarray           : 0.17.0
xlrd             : 2.0.1
xlwt             : None
numba            : 0.52.0

</details>
