A retail company is exploring machine learning algorithms to improve its customer segmentation systems. The data science team is evaluating both K-Means and K-Nearest Neighbors (KNN) algorithms but needs to understand the key differences between them, since understanding these distinctions will help the team choose the right algorithm for their specific tasks. Given this context, what do you recommend to the company?