How to choose the features for an algorithm from the given attached screenshot?
Why start with feature selection/engineering if you have so few features to begin with?

Best practice should be to include all features/variables in your first draft model and look at the accuracy, quality of resulting segments, etc.

If there is need to improve and to leave out a feature you could then use the metrics of variable importance of your chosen model (e.g. variable importance from random forest) to decide which feature was least relevant and could be discarded for a slimmer model.

In general model performance shouldn't suffer to much from including irrelevant features and therefore selection isn't the same issue as it would be for less robust models.