What happens when the value k in the k$$th nearest What happens when the value k in the k$$th nearest neighbor algorithm is increased?

The algorithm will take less data points into account when making classification decisions

The variance in the errors decreases, but learning because more specific.

The learning is more generalizible, but there will be more variance in the errors.

The algorithm will be more likely to overfit. algorithm is increased?