Before revision:  The approximation scheme is based upon the Manifold Moving Least-Squares (MMLS) . The proposed algorithm is resistant to noise in both the domain and function values. Furthermore, the approximant is shown to be smooth and of approximation order of O(h^{m+1}) for non-noisy data , where h is the mesh size with respect to the manifold domain, and m is the degree of a local polynomial approximation utilized in our algorithm.
After revision:  The approximation scheme is based upon the Manifold Moving Least-Squares approach of (Sober and Levin 2016) to reconstruct the atlas of charts and the approximation is built on-top of those charts. The resulting approximant is shown to be smooth and of approximation order of O(h^{m+1}) for non-noisy data , where h is the mesh size with respect to the manifold domain, and m is the degree of a local polynomial approximation utilized in our algorithm.