# Which machine learning algorithm to choose?

I want to choose an unsupervised algorithm which learns to predict $n$ outputs from the data, for eg. 4 coordinates (pixels) in an image. What algorithm should I choose? I think it's a 2-class classification to divide the set of points in the image as belonging to output (1) or not (0), maybe logistic regression to give the probabilities of a point being the output point. But I am confused because classification algorithms are part of supervised algorithms where we have labelled data. Should I use clustering to find 2 groups of points that can be output or not? Maybe anomaly detection to find the 4 odd points out?