This letter considers the problem of estimating expected values of functions that are inversely weighted by an unknown density using the $k$-Nearest Neighbor method. ${L_{2}}$-consistency is established. The proposed estimator is also shown to be asymptotically semiparametric efficient. Some limited Monte Carlo experiments show that the proposed estimator performs as good as alternative methods in finite sample applications.