Normalized Cut is a graph partitioning method used in image segmentation and clustering that aims to minimize the disassociation between groups while maximizing the association within groups. It evaluates the cost of cutting a graph into disjoint subsets by considering both the total edge weight connecting different groups and the total edge weight within each group.