Choose the number of neighbors 'k'. A common choice is k = 3 or 5, but this may vary depending on the dataset. Select a distance metric, such as Euclidean, Manhattan, or Minkowski distance, to measure similarity between data points. For each data point with missing values, identify its 'k' nearest neighbors based on the chosen distance metric. Impute the missing value using the mean or median of the neighbors' values for that feature.
