Because if there is one, how could you have a ROC Curve if you can't use thresholds to draw it, as it gives the output class as a certainty?
If your algorithm does not give you any other numerical scale of support for the decision, then your ROC curve has only one point.
It's not a wrong ROC, per se, but its usefulness is dubious.
So I'd say that if you don't have this scale (continuous or not), then you can't draw a ROC curve.
Luckly, most algorithms do have this scale. In SVMs it's the distance to the margin, in logistic regression it's the output probability, in decision trees it's the leaf probability, in K-NNs it's the neighborhood voting proportions, etc.