No. You cannot know the maximum error of approximation between parts of the curve that were not sampled. I can always give you any simple (and very well behaved) curve, plus a delta function in some spot that will not have been sampled. The error of approximation can then be arbitrarily large, and fplot will never know it.
Of course, the curve I suggested as a counter-example will not be continuous or even differentiable. However, if you want that property and still see fplot "fail" to see that spike, then just add a Gaussian instead of a delta function to the well-behaved function, but choose a Gaussian with an extremely small width. As such, it behaves like a delta function, but is still theoretically infinitely differentiable.
Thus you cannot assure that the error will ALWAYS be smaller than tol, for any supplied tolerance. This is a fundamental issue with virtually any computational algorithm when applied to a completely general function. You can always choose some (locally degenerate) function that will cause it to "fail" to achieve a given tolerance.