BUG: unique() casts  type `pd.Timestamp` to `numpy.datetime64`
- [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
import pandas as pd


df = pd.DataFrame({"date": ["2019-02-10", "2019-02-10", "2019-02-11"]})
df["date"] = pd.to_datetime(df["date"])

print("Type before the for cycle:")
print(type(df["date"][0]))  # pandas._libs.tslibs.timestamps.Timestamp

for day in df["date"].unique(): 
    print("Type in the loop:")
    print(type(day))  # here is a numpy.datetime64
```

which returns:

```
Type before the for cycle:
<class 'pandas._libs.tslibs.timestamps.Timestamp'>
Type in the loop:
<class 'numpy.datetime64'>
Type in the loop:
<class 'numpy.datetime64'>
```

#### Problem description

The function `unique()` should not cast the data type.

#### Expected Output

types of `df_target["date"].unique()` should be the same as in ` set(df_target["date"].to_list())`. E.g.


```python
import pandas as pd


df = pd.DataFrame({"date": ["2019-02-10", "2019-02-10", "2019-02-11"]})
df["date"] = pd.to_datetime(df["date"])

print("Type before the for cycle:")
print(type(df["date"][0])) 

for day in set(df["date"].to_list()): 
    print("Type in the loop:")
    print(type(day))
```

Returning:
```
Type before the for cycle:
<class 'pandas._libs.tslibs.timestamps.Timestamp'>
Type in the loop:
<class 'pandas._libs.tslibs.timestamps.Timestamp'>
Type in the loop:
<class 'pandas._libs.tslibs.timestamps.Timestamp'>
```

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

```
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.7.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.5.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_GB.UTF-8
LOCALE           : en_GB.UTF-8

pandas           : 1.0.5
numpy            : 1.19.0
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 47.3.1
Cython           : None
pytest           : 5.4.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.2
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.4.1
pyxlsb           : None
s3fs             : None
scipy            : 1.5.2
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None
```

</details>
