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The OP is referring to Fisher's p-value rather than the more common Neyman-Pierson method that you refer to. Fisher's method doesn't have the concept of the null hypothesis. The difference is fascinating and I do believe the Fisherian method is superior if you can't easily replicate.

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The definition of p-value is the same independent of method, as far as I can tell the only real difference is that by Neyman–Pearson you just look at whether the p-value is below a threshold, and Fisher looks at p-value as "strength of evidence" valuable in itself. It's still not the probability that your result was due to chance, it's the probability that under the null hypothesis (and you will definitely need one) you would get that value (or more extreme) by chance.

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