I might have found a solution/workaround, but if there are more compact, correct and robust methods I will accept them!
a = [{'22-Jun-2023 09:00:00'}
{'23-Jun-2023 19:00:00'}
{'24-Jun-2023 16:00:00'}
{'24-Jun-2023 11:00:00'}
{'19-Jun-2023 16:00:00'}
{'20-Jun-2023 10:00:00'}
{'21-Jun-2023 10:00:00'}
{'22-Jun-2023 09:00:00'}
{'23-Jun-2023 14:00:00'}
{'19-Jun-2023 17:00:00'}
{'20-Jun-2023 11:00:00'}
{'21-Jun-2023 17:00:00'}
{'22-Jun-2023 15:00:00'}
{'23-Jun-2023 06:00:00'}
{'24-Jun-2023 11:00:00'}
{'25-Jun-2023 19:00:00'}
{'20-Jun-2023 11:00:00'}
{'21-Jun-2023 09:00:00'}
{'23-Jun-2023 12:00:00'}
{'25-Jun-2023 17:00:00'}
{'23-Jun-2023 12:00:00'}
{'22-Jun-2023 07:00:00'}];
% Get datetime from cells
b = datetime(a,'InputFormat','dd-MMM-yyyy HH:mm:ss','Format','dd-MMM-yyyy');
c = dateshift(b, 'start', 'day');
% Get unique dates
[~, inds] = unique(datestr(c, 'yyyymmdd'), 'rows', 'stable');
uniqueDates = sort(c(inds))
uniqueDates = 7×1 datetime array
19-Jun-2023
20-Jun-2023
21-Jun-2023
22-Jun-2023
23-Jun-2023
24-Jun-2023
25-Jun-2023
% Count occurences for each date
d = groupsummary(table(c),1)
d = 7×2 table
c GroupCount
___________ __________
19-Jun-2023 2
20-Jun-2023 3
21-Jun-2023 3
22-Jun-2023 4
23-Jun-2023 5
24-Jun-2023 3
25-Jun-2023 2