Supervised Learning is a type of machine learning where a model is trained on a labeled dataset. In this context, "labeled" means that each training example is paired with an output label. The goal of supervised learning is for the model to learn the underlying patterns in the data so that it can make accurate predictions on new, unseen data.
### How Supervised Learning Works:
1. **Training Data**: The algorithm is fed a dataset that includes


