Unsupervised Learning explained in easy way

Unsupervised learning uses a table with only input columns and no output column. The input columns are the features we give the computer like height, weight, and age of people, but we do not tell it what the result should be. By studying many rows of this input data, the computer finds patterns on its own such as grouping similar people together. Later, these groups help us understand the data better without any predefined answers. This type of learning is called unsupervised learning.