Supervised learning is an aspect of machine learning where the models learn from their previous experiences. A model has something called labeled training data. This labeled training data consists of various data sets which are labeled. Each data set has a set of inputs typically a vector and the desired output called as the supervisory signal. A supervised learning algorithm analyzed these training data sets and produces an inferred function which determines the possible outcome of the new examples.
To learn more about supervised learning read this blog on Supervised learning.