Differentiate between Supervised learning and Unsupervised learning, give suitable example for each.

Supervised learning and unsupervised learning are two fundamental paradigms in machine learning, each serving distinct purposes in pattern recognition and data analysis.

Supervised Learning: Supervised learning involves training a model on a labeled dataset, where the input data is paired with corresponding target labels. The goal is for the model to learn the relationship between inputs and outputs so that it can make accurate predictions _______ _________ ______ _____ ___ _________.
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