Why using KNN ?

KNN is an algorithm that is useful for matching a point with its closest k neighbors in a multi-dimensional space. It can be used for data that are continuous, discrete, ordinal and categorical which makes it particularly useful for dealing with all kind of missing data.

The assumption behind using KNN for missing values is that a point value can be approximated by the values of the points that are closest to it, based on other variables.