Using nearest neighbor, we have an unclassified object and a set of objects that are classified. We then take the attributes of the unclassified object, compare against the known classifications in place, and select the class that is closest to our unknown. The comparison distances resolve to Euclidean geometry computing the distances between two points (where known attributes fall in comparison to the unknown's attributes).