BUG: groupby with dropna=False and 'unique' aggregate creates duplicated index
- [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
df_list = [[1, 1, 1, 'A'], [1, None, 1, 'A'], [1, None, 2, 'A'], [1, None, 3, 'A']]
df_dropna = pd.DataFrame(df_list, columns=["a", "b", "c", 'partner'])

# with 'unique', groupby result contains duplicates
partners =\
    df_dropna.groupby(['a', 'b', 'c'], dropna=False)\
    .agg({'partner': ['nunique', 'unique']})
partners.index.is_unique

# when using another aggregate function than 'unique', it is working as expected
partners =\
    df_dropna.groupby(['a', 'b', 'c'], dropna=False)\
    .agg({'partner': ['nunique', 'sum']})
partners.index.is_unique
```

#### Problem description

When using 'unique' and another aggregate function in case of a groupby on key containing NA values, the result index contains duplicates but it shouldn't:

```
        partner       
        nunique unique
a b   c               
1 1.0 1       1    [A]
  NaN 1       1    [A]
      2       1    [A]
      3       1    [A]
      1       1    [A]
      2       1    [A]
      3       1    [A]
```

#### Expected Output

Groupby result index shouldn't contain duplicates as below:
```
        partner       
        nunique unique
a b   c               
1 1.0 1       1    [A]
  NaN 1       1    [A]
      2       1    [A]
      3       1    [A]
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
python           : 3.8.10.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19042
machine          : AMD64
processor        : AMD64 Family 23 Model 96 Stepping 1, AuthenticAMD
byteorder        : little
LC_ALL           : None
LANG             : en
LOCALE           : English_United Kingdom.1252

pandas           : 1.2.4
numpy            : 1.20.3
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.1.2
setuptools       : 49.6.0.post20210108
Cython           : None
pytest           : 6.2.2
hypothesis       : None
sphinx           : 4.0.2
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.2
html5lib         : None
pymysql          : None
psycopg2         : 2.8.6 (dt dec pq3 ext lo64)
jinja2           : 3.0.1
IPython          : 7.24.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.2
numexpr          : None
odfpy            : None
openpyxl         : 3.0.5
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : 1.3.22
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
