# Why in spectral clustering number of eigen vectors is same as number of clusters that we want?

In spectral clustering we take eigenvector corresponding to K smallest eigenvalues. Then we do K means clustering on these eigenvector to get final clusters. What will happen if we take different number of eigenvectors than number of clusters we want ?