Different between supervised and unsupervised learning algorithm

I have got one doubt in the week-1 unsupervised learning part-1 third example (Grouping customers)
my doubt is that in unsupervised learning the data is unlabeled but in this example while seeing a student X joined because he/she wants to grow skills and knowledge and student Y joined to develop his career…etc aren’t these data examples seem to be labeled already .
I know I am wrong but how there is something I didn’t understand but I see while saying someone’s name and age and other features and he joined for growing skills is a labeled data

Thanks in advance

@Ahmad_Alkhuder, welcome to the community!

The important thing to remember in this example (or any time you’re choosing what ML approach to use), is to think about what problem you are trying to answer.

With supervised learning, you are trying to predict some “label” value for new input data based on what we’ve seen from other examples where we know that label value. So, if our goal was to predict why some new student, Z, was taking the class based on knowing what previous students reasons for taking the class were, then supervised learning would be appropriate. For example, if we had name, age, and other features for student Z, and those same features plus reason for taking the class for the other students, as you suggest.

But, that’s not our goal in this example. In this example, we want to take the information we have about a set of students and look at it to see what natural clusters or groups we notice. Then, we can look at the groups and see what can tell about those groups that distinguishes them. The goal is to figure out what the groups are - knowing this can help in making sure courses focus on the various interests of the students.