With a classifier, it is possible for us to learn an inference to a non-observable feature or class based on features of the objects. Thus, given a new object, we can determine this class based on the learned association.
This is illustrated by the following scenario:
A blindfolded person draws balls from the urn and is told what color the ball is. At the same time the person perceives the surface structure and the weight. Because the green balls are always heavy or medium-heavy in combination with a rough surface and the red balls are light and smooth or medium-heavy and smooth, the person is able to determine the color of the drawn ball himself after only 20 balls. Now the person acts as a classifier, who has learned from history to recognize the ball color on the basis of other features.
By a classifier we understand an algorithm, which assigns an object, which we consider, to one of the given classes.