The Set Covering Problem is a classic optimization problem in computer science and operations research. It involves selecting a minimum number of subsets from a given collection so that their union covers all elements in a universal set. Each subset has a cost associated with it, and the goal is to minimize the total cost while ensuring complete coverage. This problem can be applied in various fields, such as network design, resource allocation, and facility location. It is known to be NP-hard, meaning that finding an exact solution efficiently for large instances is challenging. Approximation algorithms are often used to find near-optimal solutions.