Graph Cuts is a technique used in computer science and image processing to segment images or partition data into distinct regions. It represents the problem as a graph, where nodes correspond to pixels or data points, and edges represent the relationships between them. The goal is to find a cut that minimizes the cost, effectively separating the graph into two parts. This method is particularly useful in applications like image segmentation, where it helps identify objects within an image by minimizing the difference between the segments. By optimizing the cut, Graph Cuts can produce clear and accurate boundaries, making it a valuable tool in various fields, including computer vision and machine learning.