The correct answer is C. To perform unsupervised learning.
K-means clustering is a type of unsupervised learning. Unsupervised learning is a type of machine learning in which the algorithm does not have labeled data to learn from. Instead, the algorithm must find patterns in the data on its own. K-means clustering does this by finding groups of data points that are similar to each other.
A. To minimize prediction errors is not the primary purpose of k-means clustering. K-means clustering is not used to make predictions. It is used to find groups of data points that are similar to each other.
B. To group similar data points is the primary purpose of k-means clustering. K-means clustering finds groups of data points that are similar to each other.
D. To visualize data relationships is not the primary purpose of k-means clustering. K-means clustering can be used to visualize data relationships, but this is not its primary purpose.