Extrapolation: is about the relation between the new inputs where the function will be evaluated and the inputs used for training. It doesn't say anything about the relation between the function and the training inputs, as interpolation does: you can extrapolate using an interpolating function (i.e. that goes exactly through the training inputs) or an approximating function (i.e. that goes close to the training inputs). Extrapolation means that the new inputs are "outside the region delimited by the examples we used for training (the observation range)", for example one could say that extrapolation is evaluating a learned function outside the convex-hull of the inputs used for training (this example applies only if the input set has a notion of "inside" and "outside", which is the case in many many situations).
Hence, the complement of extrapolation would be intrapolation, whether we are suing an interpolant or not. I think this makes the jargon cleaner!
interpolation <-----> approximation----->
intrapolation <-----> extrapolation----->