When using an unsupervised alogirthm, what is the "learning" part since it belong to machine learning field? I had a brief experience with machine learning by using a clustering algorithm, i also read the basic ideas and calculations of a simple classification algorithm.
Now, i would read more about &quot;machine learning&quot; and I found many similar definitions like the following:

&quot;Machine learning is the science of getting computers to act without being explicitly programmed...&quot;
&quot;Machine learning is a type of artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed... &quot;

My understanding is that the ability to learn and adapting deduction (output) without reprogrammation is the main idea, and based on my personal understanding, this &quot;adaptation&quot; is only possible with &quot;supervised algorithm&quot; with a new training which can permit a change/adaptation/improvement on the output model with the same program and source code.
So based on my understanding again, this &quot;adaptation&quot; and &quot;learning&quot; definition doesn't fit unsupervised machine learning algorithms, since the model with all calculations is fixed and implemented! Any change will need an update on source code!
Therefore, I would have corrections to my misinterpretation, and more clarifications to have a better understanding of &quot;machine learning&quot; and unsupervised/supervised learning relation.
You said:


  and based on my personal understanding, this "adaptation" is only possible with "supervised algorithm"


However, it is not true. Let's consider a clustering method as an unsupervised algorithm like K-means. Each iteration in K-means algorithm is a basis for the next iteration of the K-means up to the convergence of the algorithm. Hence, it means we are learning the structure of the data in each iteration up to reaching a specific target value. Although it is unsupervised, we are learning the structure of the data in each iteration. Indeed, it is a kind of (unsupervised) learning at all.