We warmly invite all members of the AI Horizon Community to join and participate in this insightful session. This workshop focused on the K Nearest Neighbors (KNN) algorithm, where members explored both the fundamental concepts and practical implementation of the model in an interactive and easy to understand manner. Participants learned how the KNN algorithm works for both classification and regression tasks, including distance calculation methods, neighbor selection, prediction techniques, and the impact of different values of K on model performance. Beyond the theoretical introduction, members also performed manual computations and predicted results using simple multi feature datasets for both regression and classification problems. The session provided a hands on learning experience that helped participants strengthen their understanding of machine learning fundamentals, data-driven prediction techniques, and real world applications of KNN in AI and Machine Learning.