A framework for Iterative Learning Control (ILC) is proposed for the situation when the ILC algorithm is based on an estimate of the controlled variable obtained from an observer-based estimation procedure. Under the assumption that the ILC input converges to a bounded signal, a general expression for the asymptotic error of the controlled variable is given. The asymptotic error is then exemplified by an ILC algorithm applied to a flexible two-mass model of a robot joint.