REGR: fillna not filling NaNs after pivot without explicitly listing pivot values
- [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.

---

Hi,

I have this (simplified) piece of code which seems to have stopped working correctly in Pandas 1.1:

```python
import pandas as pd

data = [
    [1, 1, 1, 1.],
    [2, 2, 2, 2.],
    [3, 3, 3, 3.],
]

df = pd.DataFrame(data, columns=['i1', 'i2', 'i3', 'f1'])
df = df.pivot('i1', 'i2')
df = df.fillna(0)
print(df)

```

#### Problem description

This is the output in Pandas 1.1.2:
```
     i3             f1
i2    1    2    3    1    2    3
i1
1   1.0  NaN  NaN  1.0  0.0  0.0
2   NaN  2.0  NaN  0.0  2.0  0.0
3   NaN  NaN  3.0  0.0  0.0  3.0
```

It contains NaNs after using fillna. It can be fixed by explicitly providing remaining columns as values to pivot (which should be the default):
`df = df.pivot('i1', 'i2', values=['i3', 'f1'])`

It also works if all columns are of the same type, like when I change f1 to contain ints instead of floats. In that case I don't need to specify the values.

#### Expected Output

This is the output on Pandas 1.0.5 and 0.25.3:
```
     i3             f1
i2    1    2    3    1    2    3
i1
1   1.0  0.0  0.0  1.0  0.0  0.0
2   0.0  2.0  0.0  0.0  2.0  0.0
3   0.0  0.0  3.0  0.0  0.0  3.0
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : 2a7d3326dee660824a8433ffd01065f8ac37f7d6
python           : 3.7.8.final.0
python-bits      : 32
OS               : Windows
OS-release       : 10
Version          : 10.0.18362
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 9, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : C.UTF-8
LOCALE           : None.None

pandas           : 1.1.2
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.3
setuptools       : 50.3.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.5.2
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.18.1
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.2
sqlalchemy       : 1.3.18
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None
None

</details>
