The Customer Segmentation project involves using Unsupervised Machine Learning Algorithms to Cluster Customers into distinct groups based on their shared characteristics and behaviors. The project involves collecting and preprocessing customer data, such as purchase history, demographic information, and website activity, and applying Clustering algorithms such as K-means or hierarchical clustering to group customers based on similarities in their behavior. The resulting clusters can then be analyzed to identify patterns and trends in customer behavior, which can be used to develop targeted marketing campaigns and improve overall customer engagement. The Project may also involve evaluating the performance of different clustering algorithms and selecting the optimal approach based on the quality of the resulting Customer segments.