The Full Form of KNN is‍ k-nearest neighbors.

The k-nearest neighbors (KNN) algorithm is a simple, easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. Pause! Let us unpack that.

A supervised machine learning algorithm (as opposed to an unsupervised machine learning algorithm) is one that relies on labeled input data to learn a function that produces an appropriate output when given new unlabeled data.

Imagine a computer is a child, we are its supervisor (e.g. parent, guardian, or teacher), and we want the child (computer) to learn what a pig looks like. We will show the child several different pictures, some of which are pigs and the rest could be pictures of anything (cats, dogs, etc).

When we see a pig, we shout “pig!” When it’s not a pig, we shout “no, not pig!” After doing this several times with the child, we show them a picture and ask “pig?” and they will correctly (most of the time) say “pig!” or “no, not pig!” depending on what the picture is. That is supervised machine learning.